One-sample survival tests in the presence of non-proportional hazards in oncology clinical trials

[2506.18608] One-sample survival tests in the presence of non-proportional hazards in oncology clinical trials Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Statistics > Applications arXiv:2506.18608 (stat) [Submitted on 23 Jun 2025 ( v1 ), last revised 9 Apr 2026 (this version, v3)] Title: One-sample survival tests in the presence of non-proportional hazards in oncology clinical trials Authors: Chloé Szurewsky (U1018 (Équipe 2)), Guosheng Yin (DSAS), Gwénaël Le Teuff (U1018 (Équipe 2)) View a PDF of the paper titled One-sample survival tests in the presence of non-proportional hazards in oncology clinical trials, by Chlo\'e Szurewsky (U1018 (\'Equipe 2)) and 2 other authors View PDF HTML (experimental) Abstract: In oncology, conduct well-powered time-to-event randomized clinical trials may be challenging due to limited patietns number. Many designs for single-arm trials (SATs) have recently emerged as an alternative to overcome this issue. They rely on the (modified) one-sample log-rank test (OSLRT) under the proportional hazards to compare the survival curves of an experimental and an external control group. We extend Finkelstein's formulation of OSLRT as a score test by using a piecewise exponential model for early, middle and delayed treatment effects and an accelerated hazards model for crossing hazards. We adapt the restricted mean survival time based test and construct a combination test procedure (max-Combo) to SATs. The performance of the developed are evaluated through a simulation study. The score tests are as conservative as the OSLRT and have the highest power when the data generation matches the model underlying score tests. The max-Combo test is more powerful than the OSLRT whatever the scenarios and is thus an interesting approach as compared to a score test. Uncertainty on the survival curve estimated of the external control group and its model misspecification may have a significant impact on performance. For illustration, we apply the developed tests on real data examples. Subjects: Applications (stat.AP) ; Methodology (stat.ME) Cite as: arXiv:2506.18608 [stat.AP] (or arXiv:2506.18608v3 [stat.AP] for this version) https://doi.org/10.48550/arXiv.2506.18608 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Chloé Szurewsky [ view email ] [via CCSD proxy] [v1] Mon, 23 Jun 2025 13:12:39 UTC (2,339 KB) [v2] Thu, 23 Oct 2025 08:37:55 UTC (6,630 KB) [v3] Thu, 9 Apr 2026 08:14:58 UTC (4,558 KB) Full-text links: Access Paper: View a PDF of the paper titled One-sample survival tests in the presence of non-proportional hazards in oncology clinical trials, by Chlo\'e Szurewsky (U1018 (\'Equipe 2)) and 2 other authors View PDF HTML (experimental) TeX Source view license Current browse context: stat.AP < prev | next > new | recent | 2025-06 Change to browse by: stat stat.ME References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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